NDLI: AUTOBIB: automatic extraction of bibliographic information on the Web

Content Provider	IEEE Xplore Digital Library
Author	Junfei Geng Jun Yang
Copyright Year	2004
Description	Author affiliation: Dept. of Comput. Sci., Duke Univ., Durham, NC, USA (Junfei Geng; Jun Yang)
Abstract	The Web has greatly facilitated access to information. However, information presented in HTML is mainly intended to be browsed by humans, and the problem of automatically extracting such information remains an important and challenging task. In this work, we focus on building a system called AUTOBIB to automate extraction of bibliographic information on the Web. We use a combination of bootstrapping, statistical, and heuristic methods to achieve a high degree of automation. To set up extraction from a new site, we only need to provide a few lines of code specifying how to download pages containing bibliographic information. We do not need to be concerned with each site's presentation format, and the system can cope with changes in the presentation format without human intervention. AUTOBIB bootstraps itself with a small seed database of structured bibliographic records. For each bibliographic Web site, we identify segments within its pages that represent bibliographic records, using state-of-the-art record-boundary discovery techniques. Next, we find matches for some of these "raw records" in the seed database using a set of heuristics. These matches serve as a training set for a parser based on the hidden Markov model (HMM), which is then used to parse the rest of the raw records into structured records. We have found an effective HMM structure with special states that correspond to delimiters and HTML tags in raw records. Experiments demonstrate that for our application, this HMM structure achieves high success rates without the complexity of previously proposed structures.
Sponsorship	Oracle Portugal
Starting Page	193
Ending Page	204
File Size	560182
Page Count	12
File Format	PDF
ISBN	0769521681
ISSN	10988068
DOI	10.1109/IDEAS.2004.1319792
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-09
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Hidden Markov models Humans HTML Computer science Databases Training data Automation Engineering profession Programming profession
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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